There has been a significant increase in the use of Wi-Fi and Bluetooth devices, and this trend is likely to continue with adoption of WiMax and city-wide mesh networks. As the possibility of overcrowding the Industrial-Scientific-Medical (ISM) bands of the radio frequency (RF) spectrum—such as the 2.4 GHz band—increases with a growing number of wireless devices, cognitive radios try to alleviate utilization pressure on affected bands. A cognitive radio constantly senses the spectrum and opportunistically utilizes unused frequencies in target portions of the spectrum. For example, some portions of the spectrum are underutilized, i.e., only about 5% of the spectrum from 30 MHz to 30 GHz is used at any one time in the U.S. Additionally, television bands from 470 MHz to 698 MHz might be opened up to unlicensed users in 2009.
A key challenge in the design of cognitive radio networks has been efficient and non-interfering spectrum allocation, which enables nodes to reserve chunks of the spectrum for certain periods of time. The problem of allocating spectrum for cognitive radio networks poses new challenges that have not arisen in traditional wireless technologies, including Wi-Fi. In particular, cognitive radios provide the capability of dynamically adjusting both the center frequency and the communication bandwidth for each transmission. In contrast, traditional wireless networks use a fixed channel bandwidth. For example, each channel in IEEE 802.11a is defined by the standard to be 20 MHz wide. Consequently, the lack of pre-defined channels prevents the use of conventional multi-channel Media Access Control (MAC) protocols for spectrum allocation in cognitive radio networks.
Extensively studied classical channel assignment and scheduling problems are also not directly applicable to the issue of spectrum allocation in cognitive radio networks. Spectrum allocation for channels of predefined bandwidth has been conventionally modeled, but modeling variable bandwidth communication is much more complicated.